Combining novel feature selection strategy and hyperspectral vegetation indices to predict crop yield

Shuaipeng Fei, Lei Li, Zhiguo Han, Zhen Chen & Yonggui Xiao
Abstract Background Wheat is an important food crop globally, and timely prediction of wheat yield in breeding efforts can improve selection efficiency. Traditional yield prediction method based on secondary traits is time-consuming, costly, and destructive. It is urgent to develop innovative methods to improve selection efficiency and accelerate genetic gains in the breeding cycle. Results Crop yield prediction using remote sensing has gained popularity in recent years. This paper proposed a novel ensemble feature selection...
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